One Proportion Test Power Calculator
Estimates approximate power for a one-proportion test. The form displays approximate normal power beside one proportion test power, using a worked condition that can be recalculated with the labeled inputs.
Set the labeled inputs
One Proportion Test Power
What one proportion test power answers
The one proportion test power page estimates approximate power for a one-proportion test.
One Proportion Test Power is limited to the statistical quantity named by the result panel. The one proportion test power calculation does not silently add a population, time horizon, causal direction, or decision threshold that is absent from the fields.
Before entering the one proportion test power data
- Planned proportion: For one proportion test power, the worked value for planned proportion is 0.6 proportion. Treat the planned proportion entry (0.6 proportion) explicitly as a count, proportion, rate, estimate, or model parameter before comparing one proportion test power conditions. The form enforces minimum 1e-06, maximum 0.999999.
- Null proportion: For one proportion test power, the worked value for null proportion is 0.5 proportion. Treat the null proportion entry (0.5 proportion) explicitly as a count, proportion, rate, estimate, or model parameter before comparing one proportion test power conditions. The form enforces minimum 1e-06, maximum 0.999999.
- Sample size: For one proportion test power, the worked value for sample size is 100 observations. Treat the sample size entry (100 observations) explicitly as a count, proportion, rate, estimate, or model parameter before comparing one proportion test power conditions. The form enforces minimum 2.
The entries used for one proportion test power must refer to one coherent analysis condition. Combining incompatible populations, periods, or measurement definitions can produce valid one proportion test power arithmetic for a nonexistent study.
Working through the one proportion test power formula
For one proportion test power, match every symbol in the relationship to a labeled field before substituting numbers. One Proportion Test Power is reported in the scale implied by the inputs and formula.
While checking one proportion test power, enter proportions on the scale expected by the labels; 0.40 and 40 are not interchangeable inputs for one proportion test power.
Verifying the default one proportion test power result
The default one proportion test power condition is Planned proportion = 0.6 proportion, Null proportion = 0.5 proportion, Sample size = 100 observations.
A planned proportion of 0.60 against 0.50 with n=100 gives approximate two-sided normal power of 0.5160 under this page's stated method.
The live calculator reports Approximate power 0.51599099. Repeating one intermediate step from approximate normal power provides a fixed one proportion test power reference check for later code changes.
Statistical context for one proportion test power
The normal approximation is sensitive to the null proportion, sample size, and whether the planned effect is substantively meaningful.
For one proportion test power, power and design calculations are prospective scenarios, not guarantees. For one proportion test power, their answer changes when the planned effect, variance, allocation, alpha, or attrition assumption changes.
How to interpret the one proportion test power output
When interpreting one proportion test power, report the design inputs as assumptions and compare at least one plausible alternative before committing resources to the plan.
As a second check for one proportion test power, confirm that Planned proportion and Sample size cover the same population and time boundary before interpreting the displayed probability or risk.
Varying a single one proportion test power input at a time
Change planned proportion while holding the remaining entries fixed, then state why the direction and size of the one proportion test power change are plausible from approximate normal power.
Repeat the one proportion test power exercise with sample size. If a modest defensible change materially alters the interpretation, report both conditions rather than presenting that one proportion test power scenario as exact.
When the analysis changes, compare two proportion test power.
Rebuilding this one proportion test power calculation later
Report one proportion test power using approximate normal power, followed by the entered values, units, exclusions, and analysis date. Name the one proportion test power population or dataset boundary instead of leaving it implicit.
Keep the full calculator output with the record, including Approximate power 0.51599099. A later one proportion test power review can then distinguish a changed input from a different convention or software implementation.
Questions about one proportion test power
How should one proportion test power be rounded?
Keep the unrounded one proportion test power for subsequent arithmetic, then report only the precision supported by the source measurements and the decision context. Extra digits in one proportion test power do not correct sampling or model error.
Which input deserves the closest boundary check?
For one proportion test power, start with sample size and then planned proportion. Confirm the one proportion test power units and allowed domain because a valid-looking entry can still describe the wrong statistical setup.
Why could another program report a different one proportion test power?
A different convention for rounding, tails, ties, interpolation, parameterization, or missing values can change one proportion test power. Compare the printed one proportion test power formula and its input definitions before treating either output as wrong.
What does one proportion test power represent on this page?
It is the quantity produced by approximate normal power from the displayed planned proportion, null proportion, sample size. This page estimates approximate power for a one-proportion test.
What should be saved with one proportion test power?
Save the entered values and units for planned proportion, null proportion, sample size, along with the analysis date, exclusions, software or formula version, and the relationship approximate normal power. That record is sufficient to rebuild this specific one proportion test power calculation.